machine-learning-

Predicting Cardiovascular Disease | The dataset consists of 70 000 records of patients data, 11 features + target. This is a classical problem.I have applied six classical algorithm ( [Random Forest Classifier, Decision Tree Classifier ,SVC , Logistic Regression, Gaussian Naïve Bayes]).Best accuracy came from SVN and Logistical Regression Which is 70% .

Data set :cardio_train.csv

code :Final.ipynb

How you can use

I uesd Anaconda which is the birthplace of Python data science. :)